DEEPFAKE EVIDENCE

A convincing image, voice message, video, or screenshot can create pressure before anyone has established what it proves. DEEPFAKE EVIDENCE offers an evidence-first field guide for making better-supported decisions when generative AI and ordinary digital editing blur the line between media, context, and claim.
André Kologeski translates forensic reasoning, digital-evidence preservation, provenance, corroboration, and deception analysis into a practical workflow. Readers learn how to preserve the item they actually received, define the proposition at stake, inspect metadata and Content Credentials without treating them as truth badges, reconstruct source and context, compare genuinely independent records, use detectors as bounded signals, and write findings that separate what is known, supported, unresolved, and unsafe to infer.
The book addresses images, audio and voice impersonation, video sequence and synchronization, online accounts and screenshots, detector limits, corroboration matrices, professional reporting, fictional case files, evidence logs, escalation requests, correction language, and an update plan for changing standards and tools.
It is designed for journalists, fact-checkers, investigators, attorneys and paralegals, fraud and risk professionals, security teams, educators, advanced students, small businesses, and serious readers facing consequential media claims.
This is a guide to disciplined verification-not a promise of certainty, certification, or a single tool that can answer every question.